Method and apparatus for calculating abdominal disease diagnosis information based on medical image

Abstract

A method for analyzing an abdominal disease based on a medical image, includes receiving and preprocessing a medical image obtained by photographing an abdominal region of a patient to detect a plurality of analysis candidate regions and setting one of the plurality of analysis candidate regions as a ROI, calculating a nodule grade based on surface unevenness of the ROI, calculating a cellular heterogeneity coefficient based on pixel homogeneity of the ROI, and predicting and outputting an abdominal disease value based on the nodule grade and the cellular heterogeneity coefficient.

Description

CROSS-REFERENCE TO RELATED APPLICATION AND CLAIM OF PRIORITY[0001]This application claims priority to Korean Patent Application No. 10-2018-0135772 filed on Nov. 7, 2018 in the Korean Intellectual Property Office (KIPO), the entire disclosure of which is incorporated by reference herein.[0002]This study was supported by the grants of the National Research Foundation of Korea (NRF) (2016M3A9A7918501) and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare (HI18C1216).BACKGROUND1. Technical Field[0003]This disclosure relates to a method and apparatus for analyzing an abdominal disease based on a medical image, and in particular, to a method and apparatus for analyzing an abdominal disease based on a medical image, which calculates a nodule grade and a cellular heterogeneity coefficient from a medical image obtained by photographing an abdominal region of a patient and simply predicts and no...

AI Technical Summary

Benefits of technology

[0011]This disclosure is to solve the above problems, and the present disclosure is directed to providing a new-type method and apparatus for analyzing an abdominal disease based on a medical image, which may calculate a nodule grade and a cellular heterogeneity coefficient from a medical image obtained by photographing an abdominal region of a patient and simply predict and notify the degree of abdominal disease by using the nodule grade and the cellular heterogeneity coefficient.

[0017]In the present disclosure, it is possible to calculate a nodule grade and a cellular heterogeneity coefficient from a medical image obtained by photographing an abdominal region of a patient and simply predicts and notifies the degree of abdominal disease by using the nodule grade and the cellular heterogeneity coefficient. In this case, since the degree of abdominal disease of the patient may be predicted and notified simultaneously with the acquisition of the medical image, it is possible to greatly reduce the cost and time required for diagnosing the degree of disease of the patient.

Problems solved by technology

If hepatitis recurs repeatedly to develop chronic hepatitis, it develops into hepatocirrhosis and leads to liver cancer within several years.

Namely, in the conventional art, in order to accurately check the liver health of a patient, an image analysis process using a CT, an MRI and an ultrasound imaging device and a liver fibrosis checking process using the ELF device and the liver fibrosis scanning device must be performed together, which however unnecessarily increases the cost and time required for diagnosing the degree of disease of the patient.

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